Rui Jiang

ProtCell connects fragmented proteomic profiles, extends information beyond measured panels, and guides more informative measurements.

scMTG reconstructs single-cell temporal dynamics from unpaired time-series data by learning cell representations and transitions, outperforming existing methods in interpolation and transition matrix inference.

RegFM improves gene regulation modeling by integrating cis-regulatory elements and trans-acting regulators in human cells, outperforming existing methods in multiple tasks.

HoloCell is a generative foundation model that integrates epigenomics, transcriptomics, and proteomics data across single-cell multi-omics modalities, demonstrating superior performance in representation learning and cross-modal generation.

HMI-Pred predicts gut microbe-host receptor interactions using deep learning, achieving high F1-scores and validating 47% of predictions through literature.

HitAnno annotates cell types in atlas-level scATAC-seq data using a hierarchical language model, accurately handling major and rare cell types across multiple settings.

This study develops bidirectional pluripotent stem cells (BPSCs) capable of generating both trophoblast and epiblast lineages, enabling the recapitulation of post-gastrula development in vitro and in vivo.